Update app.py

app.py

@@ -7,18 +7,30 @@ import gradio as gr
 import yt_dlp
 
 # Model dictionaries and lists
-roformer_models = {
+uvr5_models = {
     'BS-Roformer-Viperx-1297.ckpt': 'model_bs_roformer_ep_317_sdr_12.9755.ckpt',
     'BS-Roformer-Viperx-1296.ckpt': 'model_bs_roformer_ep_368_sdr_12.9628.ckpt',
     'BS-Roformer-Viperx-1053.ckpt': 'model_bs_roformer_ep_937_sdr_10.5309.ckpt',
-    'Mel-Roformer-Viperx-1143.ckpt': 'model_mel_band_roformer_ep_3005_sdr_11.4360.ckpt'
-}
-
-mdx23c_models = [
-    'MDX23C_D1581.ckpt',
+    'Mel-Roformer-Viperx-1143.ckpt': 'model_mel_band_roformer_ep_3005_sdr_11.4360.ckpt',
     'MDX23C-8KFFT-InstVoc_HQ.ckpt',
     'MDX23C-8KFFT-InstVoc_HQ_2.ckpt',
-]
+    'Kim_Vocal_1.onnx',
+    'Kim_Vocal_2.onnx',
+    'Kim_Inst.onnx',
+    'Reverb_HQ_By_FoxJoy.onnx',
+    'UVR-MDX-NET_Crowd_HQ_1.onnx',
+    'UVR-De-Echo-Aggressive.pth',
+    'UVR-De-Echo-Normal.pth',
+    'UVR-DeEcho-DeReverb.pth',
+    'UVR-DeNoise-Lite.pth',
+    'UVR-DeNoise.pth',
+    'UVR-BVE-4B_SN-44100-1.pth',
+    'htdemucs_ft.yaml', 
+    'htdemucs.yaml',
+    'hdemucs_mmi.yaml',
+}
+
+
 
 # More model lists...
 
@@ -51,7 +63,7 @@ def roformer_separator(audio, model, output_format, overlap, segment_size, denoi
     random_id = str(random.randint(10000, 99999))
     os.makedirs("outputs", exist_ok=True)
     write(f'{random_id}.wav', audio[0], audio[1])
-    full_roformer_model = roformer_models[model]
+    full_roformer_model = uvr5_models[model]
     
     prompt = f"audio-separator {random_id}.wav --model_filename {full_roformer_model} --output_dir=./outputs --output_format={output_format} --normalization=0.9 --mdxc_overlap={overlap} --mdxc_segment_size={segment_size}"
     if denoise:
@@ -73,9 +85,10 @@ def process_audio(url, model, output_format, overlap, segment_size, denoise):
 with gr.Blocks() as demo:
     gr.Markdown("# Hex Audio Separator")
     url_input = gr.Textbox(label="YouTube URL")
-    model_input = gr.Dropdown(choices=list(roformer_models.keys()), label="Roformer Model")
-    format_input = gr.Dropdown(choices=output_format, label="Output Format")
-    overlap_input = gr.Dropdown(choices=mdxnet_overlap_values, label="Overlap")
+    with gr.Row():
+        model_input = gr.Dropdown(choices=list(roformer_models.keys()), label="Roformer Model")
+        format_input = gr.Dropdown(choices=output_format, label="Output Format")
+        overlap_input = gr.Dropdown(choices=mdxnet_overlap_values, label="Overlap")
     segment_input = gr.Slider(0, 100, label="Segment Size")
     denoise_input = gr.Checkbox(label="Enable Denoise")